Tax-loss harvesting using correlated positions

Related Correlations Analysis

	META	MSFT	UBER	F	T	A	CRM	JPM	MRK	XOM
META		0.83	0.89	0.86	0.24	0.76	0.84	0.85	0.71	0.78	META
MSFT	0.83		0.67	0.8	0.34	0.72	0.78	0.82	0.61	0.82	MSFT
UBER	0.89	0.67		0.74	0.14	0.71	0.87	0.77	0.63	0.59	UBER
F	0.86	0.8	0.74		0.31	0.71	0.73	0.87	0.77	0.83	F
T	0.24	0.34	0.14	0.31		0.32	0.32	0.35	0.37	0.29	T
A	0.76	0.72	0.71	0.71	0.32		0.79	0.9	0.33	0.8	A
CRM	0.84	0.78	0.87	0.73	0.32	0.79		0.83	0.53	0.63	CRM
JPM	0.85	0.82	0.77	0.87	0.35	0.9	0.83		0.61	0.91	JPM
MRK	0.71	0.61	0.63	0.77	0.37	0.33	0.53	0.61		0.58	MRK
XOM	0.78	0.82	0.59	0.83	0.29	0.8	0.63	0.91	0.58		XOM
	META	MSFT	UBER	F	T	A	CRM	JPM	MRK	XOM

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Risk-Adjusted Indicators

There is a big difference between a company's stock performing well and the company itself doing well as a business compared to the competition. There are so many exceptions to the norm that investors cannot definitively determine what's good or bad unless they analyze multiple risk-adjusted performance indicators across the competitive landscape. These indicators are quantitative in nature and help investors forecast volatility and risk-adjusted expected returns across various positions.

	Mean Deviation	Jensen Alpha	Sortino Ratio	Treynor Ratio	Semi Deviation	Expected Shortfall	Potential Upside	Value @Risk	Maximum Drawdown
META	1.71	0.41	0.27	0.34	1.28	(2.12)	3.27	(2.28)	24.74
MSFT	0.93	0.07	0.06	0.12	0.98	(1.15)	2.11	(2.07)	5.31
UBER	1.58	0.16	0.13	0.14	1.35	(1.95)	2.83	(2.52)	18.39
F	1.61	(0.01)	0.02	0.05	1.87	(1.77)	4.07	(3.30)	9.61
T	0.96	(0.06)	0.00	(0.08)	0.00	0.00	2.18	(2.45)	5.92
A	1.15	0.03	0.04	0.08	1.28	(1.22)	2.26	(2.26)	6.31
CRM	1.24	(0.02)	0.00	0.04	1.96	(1.27)	2.83	(2.96)	8.61
JPM	0.78	0.05	0.04	0.09	1.31	(0.78)	1.72	(1.08)	8.65
MRK	0.64	0.05	0.06	0.12	0.64	(0.70)	1.18	(0.98)	6.92
XOM	0.83	0.27	0.26	0.57	0.62	(1.01)	1.96	(1.40)	4.66

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